Design and classification of smart metering systems for the energy diagnosis of buildings

At present, buildings account for a great share of energy consumption. It is well known that building automation control systems allow for increasing opportunities of improvement in the performance of buildings, with respect to e.g. energy performance and indoor comfort. As system within a building become more and more complex, buildings can be regarded not merely as a load but as a smart micro grid, with the possibility of actively interacting with a smart grid. In the depicted context, metering is essential for assessing the performance of management and detecting improvement opportunities. The scope of the present work is to propose a best practice for the implementation of smart metering systems in buildings and a practical methodology to classify the systems. In the present work, a novel classification protocol is devised; an existing metering system is then evaluated and an improved metering system is proposed. The proposed protocol rates the system performance via a set of weighted indicators - according to positioning of meters, measured data, system architecture, data visualization and monitored loads -, then calculates an overall grade. The protocol is tested on an existing metering system in an educational building. The metering system returns a poor rating and a number of flaws are detected thanks to the benchmark protocol. An improved metering system is then proposed which fixes existing flaws and returns a much better grade. In conclusion, the designed classification protocol allowed diagnosing an existing metering system and pinpointing improvement opportunities and it can be a useful practice in diagnostics or design of smart metering systems.